Luo has also teamed up with collaborators to protect social media users, especially young ones, against cyberbullying. The team developed a mobile cyberbullying defense system, MCDefender, that can effectively detect and prevent cyberbullying on social media.
MCDefender uses pronunciation-based convolutional neural network architecture that pre-processes data. It allows the system to detect cyberbullying, even if messages contain misspellings or words that may not be offensive individually but carry a potentially hurtful message when strung together. When the system detects cyberbullying, the would-be cyberbully gets a message encouraging him or her to think twice before hitting send. If the message is sent anyway, notifications could be sent to parents and other authorities. Should the cyberbullying persist, the social media account of the person being cyberbullied could be blurred out so that no further harm could be inflicted.
The team reported its results in “MCDefender: Toward Effective Cyberbullying Defense in Mobile Online Social Networks,” a paper published in Proceedings of the 3rd ACM on International Workshop on Security And Privacy Analytics.